Proinflammatory Stress Activates Neutral Sphingomyelinase 2–Based Generation of a Ceramide-Enriched β-Cell EV Subpopulation
Bibliographic record
Abstract
β-Cell extracellular vesicles (EVs) play a role as paracrine effectors in islet health, yet mechanisms connecting β-cell stress to changes in EV cargo and potential impacts on diabetes remain poorly defined. We hypothesized that β-cell inflammatory stress engages neutral sphingomyelinase 2 (nSMase2)-dependent EV formation pathways, generating ceramide-enriched small EVs that could impact surrounding β-cells. Consistent with this, proinflammatory cytokine treatment of INS-1 β-cells and human islets concurrently increased β-cell nSMase2 and ceramide abundance, as well as small EV ceramide species. Direct chemical activation or genetic knockdown of nSMase2, chemical treatment to inhibit cell death pathways, or treatment with a glucagon-like peptide-1 (GLP-1) receptor agonist also modulated β-cell EV ceramide. RNA sequencing of ceramide-enriched EVs identified a distinct set of miRNAs linked to β-cell function and identity. EV treatment from cytokine-exposed parent cells inhibited peak glucose-stimulated insulin secretion in wild-type recipient cells; this effect was abrogated when using EVs from nSMase2 knockdown parent cells. Finally, plasma EVs in children with recent-onset type 1 diabetes showed increases in multiple ceramide species. These findings highlight nSMase2 as a regulator of β-cell EV cargo and identify ceramide-enriched EV populations as a contributor to EV-related paracrine signaling under conditions of β-cell inflammatory stress and death. ARTICLE HIGHLIGHTS: Mechanisms connecting β-cell stress to extracellular vesicle (EV) cargo and diabetes are poorly defined. Does β-cell inflammatory stress engage neutral sphingomyelinase 2 (nSMase2)-dependent EV formation to generate ceramide-enriched small EVs? Proinflammatory cytokines increased β-cell small EV ceramide via increases in nSMase2. Ceramide-enriched EVs housed distinct cargo linked to insulin signaling, and ceramide species were enriched in plasma EVs from individuals with type 1 diabetes. Ceramide-enriched EV populations are a potential contributor to β-cell EV-related paracrine signaling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".